Search Results (291)

Massachusetts Bay in the northeastern United States is highly vulnerable to ocean acidification (OA) due to reduced buffering capacity from significant freshwater inputs. We hypothesize that acidification varies across temporal and spatial scales, with short-term variability driven by seasonal biological respiration, precipitation–evaporation balance, and river discharge, and long-term changes linked to global warming and river flux shifts. These patterns arise from complex nonlinear interactions between physical and biogeochemical processes. To investigate OA variability, we applied the Northeast Biogeochemistry and Ecosystem Model (NeBEM), a fully coupled three-dimensional physical–biogeochemical system, to Massachusetts Bay and Boston Harbor. Numerical simulation was performed for 2016. Assimilating satellite-derived sea surface temperature and sea surface height improved NeBEM’s ability to reproduce observed seasonal and spatial variability in stratification, mixing, and circulation. The model accurately simulated seasonal changes in nutrients, chlorophyll-a, dissolved oxygen, and pH. The model results suggest that nearshore areas were consistently more susceptible to OA, especially during winter and spring. Mechanistic analysis revealed contrasting processes between shallow inner and deeper outer bay waters. In the inner bay, partial pressure of pCO₂ (pCO₂) and aragonite saturation (Ω_a) were influenced by sea temperature, dissolved inorganic carbon (DIC), and total alkalinity (TA). TA variability was driven by nitrification and denitrification, while DIC was shaped by advection and net community production (NCP). In the outer bay, pCO₂ was controlled by temperature and DIC, and Ω_a was primarily determined by DIC variability. TA changes were linked to NCP and nitrification–denitrification, with DIC also influenced by air–sea gas exchange. Full article

Current treatment methods for desulfurization wastewater in the ship exhaust gas cleaning (EGC) system face several problems, including process complexity, unstable performance, large spatial requirements, and high energy consumption. This study investigates rotating dynamic filtration (RDF) as an efficient treatment approach through experimental testing, theoretical analysis, and pilot-scale validation. Flux increases with temperature and pressure but decreases with feed concentration, remaining unaffected by circulation flow. For a small membrane (152 mm), flux consistently increases with rotational speed across all pressures. For a large membrane (374 mm), flux increases with rotational speed at 300 kPa but firstly increases and then decreases at 100 kPa. Filtrate turbidity in all experiments complies with regulatory standards. Due to the unique hydrodynamic characteristics of RDF, back pressure reduces the effective transmembrane pressure, whereas shear force mitigates concentration polarization and cake layer formation. Separation performance is governed by the balance between these two forces. The specific energy consumption of RDF is only 10–30% that of cross-flow filtration (CFF). Under optimized pilot-scale conditions, the wastewater was concentrated 30-fold, with filtrate turbidity consistently below 2 NTU, outperforming CFF. Moreover, continuous operation proves more suitable for marine environments. Full article

Obesity and related metabolic disorders are closely linked to dysregulated lipid metabolism, where the metabolic balance of diacylglycerol (DAG) played a pivotal role. Although cis-palmitoleic acid (cPOA) exhibits anti-obesity effects, its efficacy varies across dietary conditions, and its molecular mechanisms remains unclear. In this study, we investigated the dose-dependent regulatory effects of cPOA on DAG metabolic shunting in db/db mice, employing lipidomics, pathway analysis, and gene/protein expression assays. Under a basal diet, low-dose cPOA (75 mg/kg) inhibited DAG-to-triglyceride (TAG) conversion, reducing hepatic lipid accumulation, while medium-to-high doses (150–300 mg/kg) redirected DAG flux toward phospholipid metabolism pathways (e.g., phosphatidylcholine [PC] and phosphatidylethanolamine [PE]), significantly lowering body weight and adiposity index. In high-fat diet (HFD)-fed mice, cPOA failed to reduce body weight but alleviated HFD-induced hepatic pathological damage by suppressing DAG-to-TAG conversion and remodeling phospholipid metabolism (e.g., inhibiting PE-to-PC conversion). Genetic and protein analyses revealed that cPOA downregulated lipogenic genes (SREBP-1c, SCD-1, FAS) and upregulated fatty acid β-oxidation enzymes (CPT1A, ACOX1), while dose-dependently modulating DGAT1, CHPT1, and PEMT expression to drive DAG metabolic shunting. Notably, DAG(36:3, 18:1–18:2) emerged as a potential biomarker for HFD-aggravated metabolic dysregulation. This study elucidated cPOA as a bidirectional regulator of lipid synthesis and oxidation, improving lipid homeostasis through dose-dependent DAG metabolic reprogramming. These findings provide novel insights and strategies for precision intervention in obesity and related metabolic diseases. Full article

Traumatic brain injury (TBI) is a major neurological condition affecting millions of individuals each year. Mild TBI (mTBI) manifests differently, with some individuals experiencing persistent, debilitating symptoms while others recover more rapidly. Despite its classification as “mild,” mTBI leads to both short- and long-term neurological effects, many of which occur due to functional changes in the brain. TBI-induced environmental changes within the brain play a critical role in shaping these functional outcomes. The importance of astrocytes in maintaining central nervous system (CNS) homeostasis has been increasingly recognized for their pivotal role in the brain’s response to TBI. Previous studies showed significant TBI-associated metabolic dysregulations. Therefore, we sought to analyze how astrocytes might adapt to persistent metabolic stressors in the post-injury microenvironment and identify injury-induced shifts occurring in vivo that may contribute to chronic metabolic dysfunction. We used an astrocyte-specific genome-scale metabolic model that allowed for the input of biologically relevant uptake rates corresponding to healthy astrocytes to analyze how the activity of metabolic pathways differed in hypoxic and acidic conditions. Additionally, these fluxes were integrated with mass spectrometry-based proteomics from male Sprague-Dawley rats subjected to mTBI to identify chronic adaptive neural responses post-injury. Comparison of modeled metabolic fluxes and experimental proteomic data demonstrated remarkable alignment, with both predicting significant changes in key metabolic processes including glycolysis, oxidative phosphorylation, the TCA cycle, and the Pentose Phosphate Pathway. These overlapping signatures may represent core survival strategies, offering insight into metabolic priorities and potentially serving as biomarkers of injury adaptation or recovery capacity. Full article

Elite soccer places significant neuromuscular and metabolic stress on athletes, leading to elevated production of reactive oxygen and nitrogen species (RONS), particularly in skeletal muscle, where intense contractile activity and increased oxygen flux drive oxidative processes. These reactive species play a dual role in skeletal muscle, supporting adaptive signaling at controlled levels while causing oxidative damage when poorly regulated. This paper presents an integrated synthesis of current knowledge on redox biology in elite soccer players, focusing on the origins and regulation of RONS, the functions of enzymatic and non-enzymatic antioxidant systems, and how both RONS and antioxidant responses influence muscle performance, fatigue, recovery, and long-term physiological adaptation. Drawing on studies conducted between 2000 and 2025, the discussion underscores the seasonal fluctuations in oxidative stress, individual variability in redox responses, and the potential adverse effects of unsystematic antioxidant supplementation. The analysis also emphasizes the value of using biomarker-guided, periodized antioxidant interventions tailored to training demands. Future directions include longitudinal tracking and the use of AI-assisted monitoring to enable personalized strategies for maintaining redox balance and optimizing performance in elite sport. Full article

Fed-batch cultivation is a widely used strategy for microbial lipid production, offering flexibility in nutrient control and the potential for high lipid productivity. However, optimizing feeding strategies remains a complex challenge, as it depends on multiple factors, including strain-specific metabolism and process limitations. In this study, we developed a computational framework based on dynamic flux balance analysis and small-scale metabolic models to evaluate and optimize lipid production in Rhodosporidium toruloides strains. We proposed equations to estimate both the carbon and energy source mass feed rate ($F_{in}·s_r$) and its concentration in the feed ($s_r$) based on lipid accumulation targets, and defined minimum feeding flow rate ($F_{in}$) according to process duration. We then assessed the impact of these parameters on commonly used bioprocess metrics—lipid yield, titer, productivity, and intracellular accumulation—across wild-type and engineered strains. Our results showed that the selection of $F_{in}·s_r$ was strongly strain-dependent and significantly influenced strain performance. Moreover, for a given $F_{in}·s_r$, the specific values of $s_r$, and the resulting $F_{in}$, had distinct and non-equivalent effects on performance metrics. This methodology enables the rational pre-selection of feeding strategies and strains, improving resource efficiency and reducing the probability of failed experiments. Full article

This paper proposes a novel hybrid less-rare-earth permanent magnet (HLEPM) machine, which is designed to meet the demands of electric vehicle (EV) traction machines for high torque output and wide-speed-range high-efficiency performance. The designed machine features a unique hybrid permanent magnet arrangement, consisting of V-shaped rare-earth PMs and arc-shaped less-rare-earth PMs, respectively. The V-shaped rare-earth magnets can perform the flux-focusing effect well, not only enhancing the torque output capability but also improving the demagnetization with the standability of the arc-shaped less-rare-earth PMs during active short-circuit (ASC) conditions. First, the proposed machine is thoroughly designed and optimized to balance the torque capability and iron loss. Subsequently, the electromagnetic performance of the proposed HLEPM machine is evaluated using finite-element (FE) analysis and compared with that of a conventional double-layer V-shaped PMSM. Finally, the anti-demagnetization characteristics of the two machines under ASC conditions are analyzed in detail. The results validate the rationality and reliability of the proposed design. Full article

Global demands for sustainable energy and advanced therapeutics necessitate innovative interdisciplinary solutions. Integrated biorefining emerges as a strategic response, enabling the co-production of biofuels and pharmaceutical compounds through biomass valorization. This integrated model holds promise in enhancing resource utilization efficiency while ensuring economic viability. Our critical review methodically evaluates seven pivotal methodologies: seven key strategies: microbial metabolites, synthetic biology platforms, biorefinery waste extraction, nanocatalysts, computer-aided design, extremophiles, and plant secondary metabolites. Through systematic integration of these approaches, we reveal pivotal synergies and potential technological innovations that can propel multi-product biorefinery systems. Persistent challenges, particularly in reconciling complex metabolic flux balancing with regulatory compliance requirements, are analyzed. Nevertheless, advancements in systems biology, next-generation bioprocess engineering, and artificial intelligence-enhanced computational modeling present viable pathways for overcoming these obstacles. This comprehensive analysis substantiates the transformative capacity of integrated biorefining in establishing a circular bioeconomy framework, while underscoring the imperative of transdisciplinary cooperation to address existing technical and policy constraints. Full article

The challenge of thermally upgrading traditional stone masonry buildings is addressed through the analysis of a representative example typical of regional rural architecture in central Poland, constructed using soft silica limestone and clay mortar. These buildings, which form an important part of the local cultural heritage, are increasingly becoming the subject of interdisciplinary research and conservation initiatives. This study presents a detailed characterization of the materials and architectural features specific to this building typology. Thermal transmittance calculations were performed and analyzed, with the use of THERM 7.6.1.0 software enabling precise modeling of the wall’s heterogeneous structure. The physical and thermal properties of natural materials—particularly soft silica limestone and clay—were taken into account. The analysis included evaluation of the heat transfer coefficient, temperature distribution, and heat flux density for a reference wall model, as well as for variants with both internal and external insulation layers. The study explores thermal comfort and energy performance within the broader context of preserving and reusing historic rural buildings. Furthermore, the findings are discussed in relation to current European energy efficiency regulations and heritage protection frameworks. The scientific value of this work lies in its context-specific, material-sensitive methodology and in providing practical insight into balancing energy retrofitting with architectural conservation. Full article

Ensuring the fire resistance and thermal stability of power cables is crucial for their reliable performance in fire environments, essential for sustainable power distribution, and allowing for more time to extinguish fires and for evacuation. This study utilises numerical simulation to analyse the thermal behaviour of fire-resistant medium-voltage cable, focusing on the impact of conductor radius and material properties under external heat flux. A heat transfer model of cables with conductor radii of 3 mm, 5 mm, and 7 mm under a localised external heat flux of 750 °C was developed. The results show that smaller conductors stabilise faster (reaching the steady state at 45 min for 3 mm vs. 79 min for 7 mm) but experience higher thermal stress, with conductor temperatures peaking at 692.5 °C. Larger conductors enhance axial heat conduction, reduce steady-state temperature by up to 25%, and improve heat dissipation by over 360%. The 5 mm conductor radius provided balanced performance, lowering the temperature by 65 °C compared to 3 mm, although it remained 20.1% hotter than the 7 mm. The ceramic layer played a crucial role in reducing heat flux in the heat source section. Optimised polyethylene insulation and ceramic material improved heat retention and surface temperature control in non-heat source sections. Also, thermal resistance analysis decreased from 1.00 K/W (3 mm) to 0.65 K/W (7 mm). Among material properties, increasing ceramic thermal conductivity had a more significant impact on reducing core temperature than improving insulation. These findings provide practical recommendations for optimising conductor geometry and material properties for more fire-resistant cables. Full article

Water-capped tailings technology (WCTT) is a strategy where oil sand tailings are sequestered within a mined-out pit and overlayed with a layer of water in order to sequester tailings with the aim that the resulting pit lake will support aquatic plants and organisms over time. The Base Mine Lake Demonstration (BML) is the first full-scale demonstration of a pit lake in the Athabasca Oil Sands Region (AOSR). In the BML, the release of methane from the fluid tailings influences several key processes, including the flux of greenhouse gases, microbial oxygen consumption in the water column, and ebullition-facilitated transport of organics from the fluid tailings to the lake surface. It is hypothesized that the residual low molecular weight hydrocarbons (LMWHCs) derived from diluent naphtha used during bitumen extraction processes are the carbon sources fueling ongoing microbial methanogenesis within the BML. The aims of this study were to identify the LMWHCs in the BML fluid tailings, to elucidate their sources, and to assess the extent of biogeochemical cycling affecting them. A headspace GC/MS analysis identified 84, 44, and 56 LMWHCs (C4–C10) present in naphtha, unprocessed bitumen ore, and fluid tailings, respectively. Equilibrium mass balance assessment indicated that the vast majority (>95%) of LMWHCs were absorbed within residual bitumen rather than dissolving into tailings pore water. Such absorbed compounds would not be readily available to in situ microbial communities but would represent a long-term source for methanogenesis. Chromatographic analysis revealed that most biodegradable compounds (n-alkanes and BTEX) were present in the naphtha but not in fluid tailings or bitumen ore, implying they are sourced from the naphtha and have been preferentially biodegraded after being deposited. Among the LMWHCs observed in bitumen ore, naphtha, and fluid tailings, C2-cyclohexanes had the highest relative abundance in tailings samples, implying their relatively high recalcitrance to in situ biodegradation. Full article

This paper presents a detailed analysis of the energy dynamics of the Mediterranean tropical-like cyclone, Medicane Ianos, by using a moist static energy (MSE) budget framework. Medicanes are hybrid cyclonic systems that share characteristics of both extratropical and tropical cyclones, making their classification and prediction challenging. Using high-resolution ERA5 reanalysis data, we analyzed the life cycle of Ianos, which is one of the strongest recorded medicanes, employing the vertically integrated MSE spatial variance budget to quantify the contributions of different energy sources to the cyclone’s development. The chosen study area was approximately 2500² km², covering the entire track of the cyclone. The budget was calculated after tracking Ianos and applying Hart phase space analysis to assess the cyclone phases. The results show that the MSE budget can reveal that the cyclone development was driven by a delicate balance between convection and dynamical factors. The interplay between vertical and horizontal advection, in particular the upward transport of moist air and the lateral inflow of warm, moist air and cold, dry air, was a key mechanism driving the evolution of Ianos, followed by surface fluxes and radiative feedback. By analyzing what process contributes most to the increase in MSE variance, we concluded that Ianos can be assimilated in the tropical framework within a radius of 600 km around the cyclone center, but only during its intense phase. In this way, the budget can contribute as a diagnostic tool to the ongoing debate regarding medicanes classification. Full article

This paper proposes a two-dimensional (2D) generalized equivalent magnetic network (GEMN) model suitable for surface-mounted permanent magnet electric machines (SPEMs). The model divides the SPEM into eight types of regions: stator yoke, stator tooth body, stator tooth tips, stator slot body, stator slot openings, air gap, rotor permanent magnets, and rotor yoke. Each region is subdivided radially and tangentially into multiple 2D magnetic network units containing radial and tangential magnetic circuit parameters, forming a regular magnetic network covering all regions of the SPEM. The topology of this magnetic network remains unchanged during rotor rotation and can accommodate various surface-mounted permanent magnet structures including Halbach arrays, which enhances the generality of the model significantly. The proposed model can be used to calculate the 2D magnetic flux density distribution, winding electromotive force, electromagnetic torque, stator iron loss, and permanent magnet demagnetization in the influence of magnetic saturation, stator slotting, and current harmonic. Comparative analysis with the accurate subdomain method (ASDM) and finite element method (FEM) demonstrates that the GEMN model achieves a good balance between computational speed and accuracy, making it particularly suitable for efficient electromagnetic performance evaluation of SPEMs. Full article

As machine learning becomes more integrated into atmospheric science, XGBoost has gained popularity for its ability to assess the relative contributions of influencing factors in the atmospheric boundary layer height. To examine how these factors vary across seasons, a seasonal analysis is necessary. However, dividing data by season reduces the sample size, which can affect result reliability and complicate factor comparisons. To address these challenges, this study replaces default parameters with grid search optimization and incorporates cross-validation to mitigate dataset limitations. Using XGBoost with four years of data from the atmospheric radiation measurement (ARM) (Southern Great Plains (SGP) C1 site, cross-validation stabilizes correlation coefficient fluctuations from 0.3 to within 0.1. With optimized parameters, the R value can reach 0.81. Analysis of the C1 site reveals that the relative importance of different factors changes across seasons. Lower tropospheric stability (LTS, ~0.53) is the dominant factor at C1 throughout the year. However, during DJF, latent heat flux (LHF, 0.44) surpasses LTS (0.22). In SON, LTS (0.58) becomes more influential than LHF (0.18). Further comparisons among the four long-term SGP sites (C1, E32, E37, and E39) show seasonal variations in relative importance. Notably, during JJA, the differences in the relative importance of the three factors across all sites are lower than in other seasons. This suggests that boundary layer development in the summer is not dominated by a single factor, reflecting a more intricate process likely influenced by seasonal conditions such as enhanced convective activity, higher temperatures, and humidity, which collectively contribute to a balanced distribution of parameter impacts. Furthermore, the relative importance of LTS gradually increases from morning to noon, indicating that LTS becomes more significant as the boundary layer approaches its maximum height. Consequently, the LTS in the early morning in autumn exhibits greater relative importance compared to other seasons. This reflects a faster development of the mixing layer height (MLH) in autumn, suggesting that it is easier to retrieve the MLH from the previous day during this period. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization. Full article

The Qinghai–Tibet Plateau (QTP), a critical hydrological regulator for Asia through its extensive glacier systems, high-altitude lakes, and intricate network of rivers, exhibits amplified sensitivity to climate-driven alterations in precipitation regimes and ice mass balance. While the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have revolutionized monitoring of terrestrial water storage anomalies (TWSAs) across this hydrologically sensitive region, spatial resolution limitations (3°, equivalent to ~300 km) constrain process-scale analysis, compounded by mission temporal discontinuity (data gaps). In this study, we present a novel downscaling framework integrating temporal gap compensation and spatial refinement to a 0.25° resolution through Gated Recurrent Unit (GRU) neural networks, an architecture optimized for univariate time series modeling. Through the assimilation of multi-source hydrological parameters (glacier mass flux, cryosphere–precipitation interactions, and land surface processes), the GRU-based result resolves nonlinear storage dynamics while bridging inter-mission observational gaps. Grid-level implementation preserves mass conservation principles across heterogeneous topographies, successfully reconstructing seasonal-to-interannual TWSA variability and also its long-term trends. Comparative validation against GRACE mascon solutions and process-based hydrological models demonstrates enhanced capacity in resolving sub-basin heterogeneity. This GRU-derived high-resolution TWSA is especially valuable for dissecting local variability in areas such as the Brahmaputra Basin, where complex water cycling can affect downstream water security. Our study provides transferable methodologies for mountainous hydrogeodesy analysis under evolving climate regimes. Future enhancements through physics-informed deep learning and next-generation climatology–hydrology–gravimetry synergy (e.g., observations and models) could further constrain uncertainties in extreme elevation zones, advancing the predictive understanding of Asia’s water tower sustainability. Full article